{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Execute this cell to install dependencies\n",
    "%pip install sf-hamilton[visualization]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Exploring tracked experiments [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dagworks-inc/hamilton/blob/main/examples/experiment_management/notebook.ipynb) [![GitHub badge](https://img.shields.io/badge/github-view_source-2b3137?logo=github)](https://github.com/apache/hamilton/blob/main/examples/experiment_management/notebook.ipynb)\n",
    "\n",
    "This notebook shows how to load data from your local repository once you executed `run.py` a few times. Note that you will need to update `run_id` values to match your data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import json\n",
    "import pickle\n",
    "\n",
    "import pandas as pd\n",
    "from IPython.display import display, Image\n",
    "from hamilton.plugins.h_experiments.cache import JsonCache"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load cache created by the `ExperimentTracker` adapter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[b'ac6c1499-6674-4834-a46b-695c25ef77fc',\n",
       " b'a0bc0edf-b2b7-45cb-87d9-0af2358fe514',\n",
       " b'fdd3e8ea-973e-4d18-9853-c38a1dbc1a9b',\n",
       " b'12a38769-3e28-458c-9074-b58b67d2159b',\n",
       " b'5283272d-70ab-41e7-909e-300c85e18441',\n",
       " b'cfaa2ae9-e99c-448f-b584-2237a1b0cbca']"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiment_cache = JsonCache(\"./experiments\")\n",
    "experiment_cache.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Get experiment from cache"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "{'config': {'model': 'linear', 'preprocess': 'pca'},\n",
       " 'date_completed': '2024-04-15T09:33:14.071273',\n",
       " 'experiment': 'forecast',\n",
       " 'graph_hash': 'e05e7ce996e5aea287f871cd118866b49b8c75cac8b1359085e85468b927b9c9',\n",
       " 'inputs': [{'default_value': 5, 'name': 'n_components', 'value': 10},\n",
       "  {'default_value': 3, 'name': 'n_splits', 'value': 3}],\n",
       " 'materialized': [{'data_saver': 'PickleSaver',\n",
       "   'path': '/home/tjean/projects/dagworks/hamilton/examples/experiment_management/experiments/forecast/cfaa2ae9-e99c-448f-b584-2237a1b0cbca/trained_model.pickle',\n",
       "   'sink': 'pickle',\n",
       "   'source_nodes': ['trained_model']},\n",
       "  {'data_saver': 'PandasParquetWriter',\n",
       "   'path': '/home/tjean/projects/dagworks/hamilton/examples/experiment_management/experiments/forecast/cfaa2ae9-e99c-448f-b584-2237a1b0cbca/prediction_df.parquet',\n",
       "   'sink': 'parquet',\n",
       "   'source_nodes': ['prediction_df']},\n",
       "  {'data_saver': 'JSONDataSaver',\n",
       "   'path': '/home/tjean/projects/dagworks/hamilton/examples/experiment_management/experiments/forecast/cfaa2ae9-e99c-448f-b584-2237a1b0cbca/cv_scores.json',\n",
       "   'sink': 'json',\n",
       "   'source_nodes': ['cv_scores_json_build_result']},\n",
       "  {'data_saver': 'MatplotlibWriter',\n",
       "   'path': '/home/tjean/projects/dagworks/hamilton/examples/experiment_management/experiments/forecast/cfaa2ae9-e99c-448f-b584-2237a1b0cbca/prediction_plot.png',\n",
       "   'sink': 'plt',\n",
       "   'source_nodes': ['prediction_plot']}],\n",
       " 'modules': ['analysis'],\n",
       " 'overrides': [],\n",
       " 'run_dir': '/home/tjean/projects/dagworks/hamilton/examples/experiment_management/experiments/forecast/cfaa2ae9-e99c-448f-b584-2237a1b0cbca',\n",
       " 'run_id': 'cfaa2ae9-e99c-448f-b584-2237a1b0cbca',\n",
       " 'success': True}"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "run_id = b\"cfaa2ae9-e99c-448f-b584-2237a1b0cbca\"\n",
    "\n",
    "experiment = json.loads(experiment_cache.read(run_id))\n",
    "\n",
    "display(\n",
    "    Image(filename=f\"{experiment['run_dir']}/dag.png\"),\n",
    "    experiment,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load materialized values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'data_saver': 'PickleSaver',\n",
       " 'path': '/home/tjean/projects/dagworks/hamilton/examples/experiment_management/experiments/forecast/cfaa2ae9-e99c-448f-b584-2237a1b0cbca/trained_model.pickle',\n",
       " 'sink': 'pickle',\n",
       " 'source_nodes': ['trained_model']}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiment[\"materialized\"][0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>#sk-container-id-2 {\n",
       "  /* Definition of color scheme common for light and dark mode */\n",
       "  --sklearn-color-text: black;\n",
       "  --sklearn-color-line: gray;\n",
       "  /* Definition of color scheme for unfitted estimators */\n",
       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
       "  --sklearn-color-unfitted-level-3: chocolate;\n",
       "  /* Definition of color scheme for fitted estimators */\n",
       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
       "\n",
       "  /* Specific color for light theme */\n",
       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
       "  --sklearn-color-icon: #696969;\n",
       "\n",
       "  @media (prefers-color-scheme: dark) {\n",
       "    /* Redefinition of color scheme for dark theme */\n",
       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
       "    --sklearn-color-icon: #878787;\n",
       "  }\n",
       "}\n",
       "\n",
       "#sk-container-id-2 {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 pre {\n",
       "  padding: 0;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-hidden--visually {\n",
       "  border: 0;\n",
       "  clip: rect(1px 1px 1px 1px);\n",
       "  clip: rect(1px, 1px, 1px, 1px);\n",
       "  height: 1px;\n",
       "  margin: -1px;\n",
       "  overflow: hidden;\n",
       "  padding: 0;\n",
       "  position: absolute;\n",
       "  width: 1px;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
       "  border: 1px dashed var(--sklearn-color-line);\n",
       "  margin: 0 0.4em 0.5em 0.4em;\n",
       "  box-sizing: border-box;\n",
       "  padding-bottom: 0.4em;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-container {\n",
       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
       "     so we also need the `!important` here to be able to override the\n",
       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
       "  display: inline-block !important;\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       "div.sk-parallel-item,\n",
       "div.sk-serial,\n",
       "div.sk-item {\n",
       "  /* draw centered vertical line to link estimators */\n",
       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
       "  background-size: 2px 100%;\n",
       "  background-repeat: no-repeat;\n",
       "  background-position: center center;\n",
       "}\n",
       "\n",
       "/* Parallel-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item::after {\n",
       "  content: \"\";\n",
       "  width: 100%;\n",
       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
       "  flex-grow: 1;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel {\n",
       "  display: flex;\n",
       "  align-items: stretch;\n",
       "  justify-content: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  position: relative;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
       "  align-self: flex-end;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
       "  align-self: flex-start;\n",
       "  width: 50%;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
       "  width: 0;\n",
       "}\n",
       "\n",
       "/* Serial-specific style estimator block */\n",
       "\n",
       "#sk-container-id-2 div.sk-serial {\n",
       "  display: flex;\n",
       "  flex-direction: column;\n",
       "  align-items: center;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  padding-right: 1em;\n",
       "  padding-left: 1em;\n",
       "}\n",
       "\n",
       "\n",
       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
       "clickable and can be expanded/collapsed.\n",
       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
       "*/\n",
       "\n",
       "/* Pipeline and ColumnTransformer style (default) */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable {\n",
       "  /* Default theme specific background. It is overwritten whether we have a\n",
       "  specific estimator or a Pipeline/ColumnTransformer */\n",
       "  background-color: var(--sklearn-color-background);\n",
       "}\n",
       "\n",
       "/* Toggleable label */\n",
       "#sk-container-id-2 label.sk-toggleable__label {\n",
       "  cursor: pointer;\n",
       "  display: block;\n",
       "  width: 100%;\n",
       "  margin-bottom: 0;\n",
       "  padding: 0.5em;\n",
       "  box-sizing: border-box;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
       "  /* Arrow on the left of the label */\n",
       "  content: \"▸\";\n",
       "  float: left;\n",
       "  margin-right: 0.25em;\n",
       "  color: var(--sklearn-color-icon);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
       "  color: var(--sklearn-color-text);\n",
       "}\n",
       "\n",
       "/* Toggleable content - dropdown */\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content {\n",
       "  max-height: 0;\n",
       "  max-width: 0;\n",
       "  overflow: hidden;\n",
       "  text-align: left;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
       "  margin: 0.2em;\n",
       "  border-radius: 0.25em;\n",
       "  color: var(--sklearn-color-text);\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
       "  /* Expand drop-down */\n",
       "  max-height: 200px;\n",
       "  max-width: 100%;\n",
       "  overflow: auto;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
       "  content: \"▾\";\n",
       "}\n",
       "\n",
       "/* Pipeline/ColumnTransformer-specific style */\n",
       "\n",
       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator-specific style */\n",
       "\n",
       "/* Colorize estimator box */\n",
       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  /* The background is the default theme color */\n",
       "  color: var(--sklearn-color-text-on-default-background);\n",
       "}\n",
       "\n",
       "/* On hover, darken the color of the background */\n",
       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "/* Label box, darken color on hover, fitted */\n",
       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
       "  color: var(--sklearn-color-text);\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Estimator label */\n",
       "\n",
       "#sk-container-id-2 div.sk-label label {\n",
       "  font-family: monospace;\n",
       "  font-weight: bold;\n",
       "  display: inline-block;\n",
       "  line-height: 1.2em;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-label-container {\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       "/* Estimator-specific */\n",
       "#sk-container-id-2 div.sk-estimator {\n",
       "  font-family: monospace;\n",
       "  border: 1px dotted var(--sklearn-color-border-box);\n",
       "  border-radius: 0.25em;\n",
       "  box-sizing: border-box;\n",
       "  margin-bottom: 0.5em;\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-0);\n",
       "}\n",
       "\n",
       "/* on hover */\n",
       "#sk-container-id-2 div.sk-estimator:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
       "}\n",
       "\n",
       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-2);\n",
       "}\n",
       "\n",
       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
       "\n",
       "/* Common style for \"i\" and \"?\" */\n",
       "\n",
       ".sk-estimator-doc-link,\n",
       "a:link.sk-estimator-doc-link,\n",
       "a:visited.sk-estimator-doc-link {\n",
       "  float: right;\n",
       "  font-size: smaller;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1em;\n",
       "  height: 1em;\n",
       "  width: 1em;\n",
       "  text-decoration: none !important;\n",
       "  margin-left: 1ex;\n",
       "  /* unfitted */\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted,\n",
       "a:link.sk-estimator-doc-link.fitted,\n",
       "a:visited.sk-estimator-doc-link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
       ".sk-estimator-doc-link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover,\n",
       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
       ".sk-estimator-doc-link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "/* Span, style for the box shown on hovering the info icon */\n",
       ".sk-estimator-doc-link span {\n",
       "  display: none;\n",
       "  z-index: 9999;\n",
       "  position: relative;\n",
       "  font-weight: normal;\n",
       "  right: .2ex;\n",
       "  padding: .5ex;\n",
       "  margin: .5ex;\n",
       "  width: min-content;\n",
       "  min-width: 20ex;\n",
       "  max-width: 50ex;\n",
       "  color: var(--sklearn-color-text);\n",
       "  box-shadow: 2pt 2pt 4pt #999;\n",
       "  /* unfitted */\n",
       "  background: var(--sklearn-color-unfitted-level-0);\n",
       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link.fitted span {\n",
       "  /* fitted */\n",
       "  background: var(--sklearn-color-fitted-level-0);\n",
       "  border: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "\n",
       ".sk-estimator-doc-link:hover span {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link {\n",
       "  float: right;\n",
       "  font-size: 1rem;\n",
       "  line-height: 1em;\n",
       "  font-family: monospace;\n",
       "  background-color: var(--sklearn-color-background);\n",
       "  border-radius: 1rem;\n",
       "  height: 1rem;\n",
       "  width: 1rem;\n",
       "  text-decoration: none;\n",
       "  /* unfitted */\n",
       "  color: var(--sklearn-color-unfitted-level-1);\n",
       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
       "  /* fitted */\n",
       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
       "  color: var(--sklearn-color-fitted-level-1);\n",
       "}\n",
       "\n",
       "/* On hover */\n",
       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
       "  /* unfitted */\n",
       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
       "  color: var(--sklearn-color-background);\n",
       "  text-decoration: none;\n",
       "}\n",
       "\n",
       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
       "  /* fitted */\n",
       "  background-color: var(--sklearn-color-fitted-level-3);\n",
       "}\n",
       "</style><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>LinearRegression()</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" checked><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow fitted\">&nbsp;&nbsp;LinearRegression<a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.4/modules/generated/sklearn.linear_model.LinearRegression.html\">?<span>Documentation for LinearRegression</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></label><div class=\"sk-toggleable__content fitted\"><pre>LinearRegression()</pre></div> </div></div></div></div>"
      ],
      "text/plain": [
       "LinearRegression()"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.linear_model import LinearRegression\n",
    "\n",
    "def load_artifact(materialize_info, strict = False):\n",
    "    sink = materialize_info[\"sink\"]\n",
    "    path = materialize_info[\"path\"]\n",
    "    \n",
    "    if sink == \"pickle\":\n",
    "        artifact = pickle.load(open(path, \"rb\"))\n",
    "    elif sink == \"parquet\":\n",
    "        artifact = pd.read_parquet(path)\n",
    "    else:\n",
    "        if strict:\n",
    "            raise TypeError(f\"Can't load artifact of type {sink}\")\n",
    "        artifact = None\n",
    "    \n",
    "    return artifact\n",
    "\n",
    "\n",
    "model = load_artifact(experiment[\"materialized\"][0])\n",
    "model"
   ]
  }
 ],
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